Key Responsibilities
- Design, build, and optimize scalable data pipelines to support analytics and machine learning workloads
- Develop and maintain robust ETL processes for large-scale data ingestion and transformation
- Collaborate with cross-functional teams to define data requirements and deliver high-quality datasets
- Implement best practices for data governance, security, and compliance
- Optimize query performance and storage solutions for analytical workloads
- Mentor junior engineers and promote data engineering best practices
Requirements
- 7+ years of experience in data engineering or related fields
- Proficiency in Python and SQL with experience in big data technologies (e.g., Spark, Hadoop)
- Strong understanding of data pipeline architectures and ETL processes
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
- Familiarity with data modeling, warehousing, and business intelligence tools